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Cornell University

Computational Canopy Models For Precision Measurement And Adaptive Management Of Grapevine Performance

Abstract

dc:description.abstract

Effective control of winegrape fruit quality requires the simultaneous consideration of multiple response models including: the relationship between the chemical profile of harvested fruit and the organoleptic qualities of a finished wine; a mechanistic understanding of key flavor and aroma compound biosynthesis; and the role of physical vineyard parameters in these biosynthetic processes. Any attempt to predictably influence the performance of a winegrape cropping system, with respect to flavor and aroma, requires the ability to both measure the relevant physical parameters of that system and to accurately manipulate them to achieve a deliberate and quantitative response. Although the sub-discipline of precision viticulture has established that a quantitative understanding of plot-scale spatial variability can guide cultural inputs toward plot-scale consistency, the existence and small-scale spatial patterns and their effect on precision management have not been extensively studied. The experiments presented here were designed to: 1) improve the precision and increase the spatial resolution of commonly used viticultural research methods with the goal of identifying, characterizing and quantifying small-scale spatial patterns in fruiting-zone of winegrape canopies; 2) explore the impact of small-scale spatial structure on the efficacy of common plot-level cultural inputs; 3) develop methods for optimizing vineyard research and commercial production operations within known parametric spatial patterns at multiple scales; and, 4) explore the potential application of these methods in the control of a specific sunlight-sensitive compound vital to the organoleptic qualities of Riesling wine. The development and application of new computational methods for managing both the data volume of high-resolution models and the combinatorial complexities of multi-objective vineyard optimization, resulted in: new quantitative metrics for describing fruit-zone sunlight regimes; the discovery and quantification of small-scale culturally-induced microclimatic spatial patterns; the discovery that small-scale spatial patterns can negatively impact the efficacy of plotscale cultural inputs; and an enhanced understanding of the relationship between canopy microclimatic variability and concentrations of C13-norisoprenoids in Riesling grapes. To date, the software tools developed within the scope of dissertation have been adopted by researchers and winegrape growers in a dozen countries and 14 U.S. states for use in the study and optimization of crop performance and fruit metabolite profiles.

Degree

thesis:*
Name thesis:degree_name
Ph. D., Horticultural Biology
Level thesis:degree_level
Doctor of Philosophy
Discipline thesis:degree_discipline
Horticultural Biology
Grantor
Cornell University
Year dc:date.issued
2011

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Meyers, James
Committee members dc:contributor.committeemember
  • Wilcox, Wayne Frank
  • Sacks, Gavin Lavi
  • Van Es, Harold Mathijs

Subjects

dc:subject × 6

Rights

Language dc:language.iso
en_US

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1813/33547
OAI identifier oai:identifier
oai:ecommons.cornell.edu:1813/33547

Chain of custody

source
Harvested from
Cornell University
Base URL
ecommons.cornell.edu/server/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Meyers, James. Computational Canopy Models For Precision Measurement And Adaptive Management Of Grapevine Performance. Doctor of Philosophy thesis, Cornell University, 2011. https://hdl.handle.net/1813/33547